{"id":6057,"date":"2015-08-11T10:00:46","date_gmt":"2015-08-11T14:00:46","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=6057"},"modified":"2015-08-10T09:43:30","modified_gmt":"2015-08-10T13:43:30","slug":"3-levers-to-success-in-predictive-analytics","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/3-levers-to-success-in-predictive-analytics\/6057\/","title":{"rendered":"3 Levers To Success in Predictive Analytics"},"content":{"rendered":"In 15 years of experience, I have seen countless predictive models\u2014but very few useful ones. Most take too long to build, and then sit unused on the shelf. The model becomes a memory, and a bad one at that. Behind the scenes, countless hours were spent figuring out what to model, getting agreement on definitions and parameters, building the model, optimizing it and preparing for the presentation to senior management. Then \u201cboom\u201d: something goes amiss, all the effort goes down the drain, and yet another model meets its arch nemesis\u2014the shelf. Worse, the analytics group\u2019s reputation suffers for <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/3-levers-to-success-in-predictive-analytics\/6057\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>In 15 years of experience, I have seen countless predictive models\u2014but very few useful ones. Most take too long to build, and then sit unused on the shelf. The model becomes a memory, and a bad one at that. Behind the scenes, countless hours were spent figuring out what to model, getting agreement on definitions [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11],"tags":[8],"class_list":["post-6057","post","type-post","status-publish","format-standard","hentry","category-industry-news","tag-predictive-analytics"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/6057","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=6057"}],"version-history":[{"count":2,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/6057\/revisions"}],"predecessor-version":[{"id":6060,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/6057\/revisions\/6060"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=6057"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=6057"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=6057"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}